Australian_City_Stack_Overflow_R.R

library(tibble)
library(ggplot2)
library(dplyr)
library(ggrepel)
library(ggthemes)

stackR <- tribble(
       ~Aus.City,      ~R, ~TotalVisits,      ~Pop,
     "Melbourne", "23176",    "1544868", "4529496",
      "Adelaide",  "7181",     "350850", "1316779",
         "Perth",  "6942",     "517323", "2039193",
      "Canberra",  "4950",     "201914",  "424666",
    "Gold Coast",     "9",      "12711",  "624918",
      "Brisbane", "10847",     "753890", "2308720",
        "Sydney", "24726",    "1782976", "4920970",
     "Newcastle",   "138",      "15348",  "434454"
    )

stackR <-
    stackR %>%
    mutate( R = as.numeric(R),
            TotalVisits = as.numeric(TotalVisits),
            Pop = as.numeric(Pop)
    ) 
stackR <-
    stackR %>%
    mutate(prop_visits_2016 = TotalVisits/sum(stackR$TotalVisits),
           prop_visits_R = R/TotalVisits,
           norm_visits = TotalVisits/Pop,
           norm_R = R/Pop) 

#drob's plot
stackR %>%
    ggplot(aes(x = prop_visits_2016, y = prop_visits_R, label = Aus.City)) +
    geom_point() + 
    theme_light() +
    geom_text_repel() +
    ylab("% of traffic going to R questions") +
    xlab("Total traffic to city as % of 2016 visits") +
    ggtitle("R visitors to Stack Overflow")

#Population normalised plot
stackR %>%
    ggplot(aes(x = norm_visits, y = norm_R, label = Aus.City)) +
    geom_point() + 
    theme_light() +
    geom_text_repel() +
    ylab("R traffic normalised by population") +
    xlab("Total traffic to city normalised by population") +
    ggtitle("R visitors to Stack Overflow")